Learning regular sets from queries and counterexamples
Information and Computation
Matrix multiplication via arithmetic progressions
Journal of Symbolic Computation - Special issue on computational algebraic complexity
Lower Bound Methods and Separation Results for On-Line Learning Models
Machine Learning - Computational learning theory
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
The weighted majority algorithm
Information and Computation
Asking questions to minimize errors
Journal of Computer and System Sciences
Learning Sat-k-DNF formulas from membership queries
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Learning Behaviors of Automata from Multiplicity and Equivalence Queries
SIAM Journal on Computing
Learning functions represented as multiplicity automata
Journal of the ACM (JACM)
Lower bounds for the multiplicative complexity of matrix multiplication
Computational Complexity
Machine Learning
Machine Learning
Learning behaviors of automata from shortest counterexamples
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
On Learning Programs and Small Depth Circuits
EuroCOLT '97 Proceedings of the Third European Conference on Computational Learning Theory
A Note on the Query Complexity of Learning DFA (Extended Abstract)
ALT '92 Proceedings of the Third Workshop on Algorithmic Learning Theory
Lower Bounds for Matrix Product
SIAM Journal on Computing
Property Testing: A Learning Theory Perspective
Foundations and Trends® in Machine Learning
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We study polynomial time learning algorithms for Multiplicity Automata (MA) and Multiplicity Automata Function (MAF) that minimize the access to one or more of the following resources: Equivalence queries, Membership queries or Arithmetic operations in the field ${\cal F}$. This is in particular interesting when access to one or more of the above resources is significantly more expensive than the others. We apply new algebraic approach based on Matrix Theory to simplify the algorithms and the proofs of their correctness. We improve the arithmetic complexity of the problem and argue that it is almost optimal. Then we prove tight bound for the minimal number of equivalence queries and almost (up to log factor) tight bound for the number of membership queries.